Artificial intelligence (AI) has been proposed as a promising technology for computer-assisted medical decision making. Artificial neural networks (ANNs) are by far the most popular form of AI. They are computer models with a parallel structure which can duplicate learning aspects of human intelligence. Therefore, ANNs can be trained to perform medical diagnostic tasks, offering physicians a fast, consistent, an unbiased second opinion. In this paper, we present a review of applications of computer-assisted diagnostic (CAD) tools using ANNs for the prediction  of acute pulmonary embolism (PE) from radiographic and clinical findings.